Multifunctional carbon dot-based dual-channel and dual-signal sensors for ribonucleotide discrimination and Fe<sup>3+</sup> detection

Ribonucleotides and Fe<sup>3+</sup> are crucial for numerous biological processes, hence their effective discrimination and detection are imperative for the investigation of metabolic processes and the early diagnosis of diseases, yet current sensing strategies based on a single signal output are hard to fulfill the demands for practical detection accuracy. Herein, a dual-channel sensor based on copper-doped fluorescent carbon dots (Cu-CDs) as a single sensing unit has been developed for the precise discrimination of ribonucleotides. Combined with statistical analyses of the data arrays, accurate discrimination and quantification of the four most vital ribonucleotide triphosphates (ATP, CTP, UTP, and GTP) are achieved, providing a valuable reference to improve the design of complex sensor arrays. Furthermore, given the merits of dual-signal detection, a silica-based aggregation-induced emission material is further introduced as the second fluorophore. The constructed novel dual-fluorescence signal sensing system enables rapid quantitative detection (2 min) and visual semi-quantitative sensing of Fe<sup>3+</sup> with enhanced accuracy and a detection limit of 1.53 μM. Briefly, such dual-signal sensors based on Cu-CDs feature easy operation, simplicity, and accuracy, offering valuable references for the design and construction of dual-channel detection tools and hold potential for practical applications.

Authors

Institutions

Publication Details

Journal
Journal of Materials Chemistry B
Published
2025-01-01
DOI
https://doi.org/10.1039/d5tb00324e
Citations
2
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
1.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multifunctional carbon dot-based dual-channel and dual-signal sensors for ribonucleotide discrimination and Fe3+ detection

Runjie Miao, Hangrong Chen, Haifeng Sha, Wenyan Ma et al.
2 citations
Journal of Materials Chemistry B
Advanced biosensing and bioanalysis techniques
1.61
article

Multifunctional carbon dot-based dual-channel and dual-signal sensors for ribonucleotide discrimination and Fe3+ detection

Runjie Miao, Hangrong Chen, Haifeng Sha, Wenyan Ma, Yu Zhang, Yuefeng Huang
article en
2 citations

Abstract

Ribonucleotides and Fe<sup>3+</sup> are crucial for numerous biological processes, hence their effective discrimination and detection are imperative for the investigation of metabolic processes and the early diagnosis of diseases, yet current sensing strategies based on a single signal output are hard to fulfill the demands for practical detection accuracy. Herein, a dual-channel sensor based on copper-doped fluorescent carbon dots (Cu-CDs) as a single sensing unit has been developed for the precise discrimination of ribonucleotides. Combined with statistical analyses of the data arrays, accurate discrimination and quantification of the four most vital ribonucleotide triphosphates (ATP, CTP, UTP, and GTP) are achieved, providing a valuable reference to improve the design of complex sensor arrays. Furthermore, given the merits of dual-signal detection, a silica-based aggregation-induced emission material is further introduced as the second fluorophore. The constructed novel dual-fluorescence signal sensing system enables rapid quantitative detection (2 min) and visual semi-quantitative sensing of Fe<sup>3+</sup> with enhanced accuracy and a detection limit of 1.53 μM. Briefly, such dual-signal sensors based on Cu-CDs feature easy operation, simplicity, and accuracy, offering valuable references for the design and construction of dual-channel detection tools and hold potential for practical applications.

Journal of Materials Chemistry BVol. 13(22)
Chinese Academy of Sciences (CN), Shanghai Institute of Ceramics (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Shanghai Science International Cooperation Project, National Key Research and Development Program of China Stem Cell and Translational Research
Reduced inequalities
Openalex Percentile: Top 17%
Advanced biosensing and bioanalysis techniques
1.61
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.